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TIU Students — Computer Engineering 2026

AI Holographic Display System

Voice-Powered Medical Visualization

An intelligent holographic display that responds to voice commands, rendering real-time 3D anatomical models through a 100 cm LED fan — bridging AI and medical education.

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Where AI Meets Holography

HoloMed AI combines a locally-running large language model (Ollama) with a high-resolution holographic LED fan to create an interactive medical education platform. Students and educators can query anatomical structures using natural speech and receive immersive 3D visual responses.

The system integrates real-time speech recognition, AI-driven dialogue, and controlled hardware to deliver a seamless, touchless experience — purpose-built for the modern medical classroom.

4096×4096
Render Resolution
1442 LEDs
Per Blade Strip
Local AI
Ollama LLM (Offline)
AI Processing
Ollama LLM — Natural Language Understanding
Holographic Render
100cm LED Fan — 4096×4096
Voice Interface
Real-time Speech-to-Text + TTS

What the System Does

01
Voice Control

Speak naturally to query the system. Real-time speech-to-text powered by Python SpeechRecognition enables hands-free operation in clinical and classroom environments.

02
AI Understanding

An Ollama-based LLM processes queries locally — no cloud dependency — providing accurate, context-aware responses about anatomy, physiology, and medical concepts.

03
Holographic Rendering

A 100 cm LED persistence-of-vision fan renders high-resolution 3D anatomical animations, creating a floating hologram visible without special glasses or screens.

04
Audio Feedback

Text-to-speech output via gTTS / pyttsx3 delivers spoken responses in sync with visual display, creating a fully multimodal interactive experience.

What We Set Out to Achieve

1
Design and build a functional AI-powered holographic display prototype using a 100 cm LED fan as the rendering medium.
2
Implement a real-time voice interface enabling natural-language queries about anatomical structures and medical topics.
3
Integrate a locally-running LLM (Ollama) to provide accurate, offline AI responses without cloud dependency.
4
Develop a cloud-synchronized library of 3D anatomical animations playable on demand through the holographic fan.
5
Evaluate the system's effectiveness as a medical education tool through user testing with students and educators.
Project Scope
Educational use in medical training — anatomy visualization
Python as primary language for AI, voice & system integration
Voice-controlled interface with real-time Bluetooth audio
Cloud-synchronized 3D anatomical animation repository
Target users: medical students, educators, healthcare trainees
Tech Stack
Python 3 Ollama LLM SpeechRecognition gTTS / pyttsx3 Microcontroller / Serial Cloud Storage 100cm LED Fan

Meet the Builders

AS
Abdulla Salim Mahmood
ID: 120222075
Computer Engineering
Tishk International University · CE Dept.
AN
Alin Noshirwan Kanabi
ID: 120222024
Computer Engineering
Tishk International University · CE Dept.
GB
Gala Bahman Muhammed
ID: 120222041
Computer Engineering
Tishk International University · CE Dept.
Project Supervisor
Dr. Abubakir Ashir
Asst. Professor, Computer Engineering — Tishk International University

Project Information

Student Contacts
Alen Nosherwan alennosherwan@gmail.com
Gala Bahman galabahman1@gmail.com
Department
Computer Engineering Department
Faculty
Faculty of Engineering
University
Tishk International University
Location
Erbil, Kurdistan Region, Iraq
Year
Academic Year 2025 – 2026
Tishk International University
Erbil, Kurdistan Region, Iraq
Faculty of Engineering — Computer Engineering
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